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Background: The latest advancement of artificial intelligence (AI) is generative pretrained transformer large language models (LLMs). They have been trained on massive amounts of text, enabling humanlike and semantical responses to text-based inputs and requests. Foreshadowing numerous possible applications in various fields, the potential of such tools for medical data integration and clinical decision-making is not yet clear., Objective: In this study, we investigate the potential of LLMs in report-based medical decision-making on the example of acute ischemic stroke (AIS), where clinical and image-based information may indicate an immediate need for mechanical thrombectomy (MT). The purpose was to elucidate the feasibility of integrating radiology report data and other clinical information in the context of therapy decision-making using LLMs., Methods: A hundred patients with AIS were retrospectively included, for which 50% (50/100) was indicated for MT, whereas the other 50% (50/100) was not. The LLM was provided with the computed tomography report, information on neurological symptoms and onset, and patients' age. The performance of the AI decision-making model was compared with an expert consensus regarding the binary determination of MT indication, for which sensitivity, specificity, and accuracy were calculated., Results: The AI model had an overall accuracy of 88%, with a specificity of 96% and a sensitivity of 80%. The area under the curve for the report-based MT decision was 0.92., Conclusions: The LLM achieved promising accuracy in determining the eligibility of patients with AIS for MT based on radiology reports and clinical information. Our results underscore the potential of LLMs for radiological and medical data integration. This investigation should serve as a stimulus for further clinical applications of LLMs, in which this AI should be used as an augmented supporting system for human decision-making., (©Jonathan Kottlors, Robert Hahnfeldt, Lukas Görtz, Andra-Iza Iuga, Philipp Fervers, Johannes Bremm, David Zopfs, Kai R Laukamp, Oezguer A Onur, Simon Lennartz, Michael Schönfeld, David Maintz, Christoph Kabbasch, Thorsten Persigehl, Marc Schlamann. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 13.02.2025.)

Background Individuals eligible for lung cancer screening with low-dose CT face a higher cardiovascular mortality risk. Purpose To investigate the association between changes in epicardial adipose tissue (EAT) at the 2-year interval and mortality in individuals undergoing serial low-dose CT lung cancer screening. Materials and Methods This secondary analysis of the National Lung Screening Trial obtained EAT volume and density from serial low-dose CT scans using a validated automated deep learning algorithm. EAT volume and density changes over 2 years were categorized into typical (decrease of 7% to increase of 11% and decrease of 3% to increase of 2%, respectively) and atypical (increase or decrease beyond typical) changes, which were associated with all-cause, cardiovascular, and lung cancer mortality. Uni- and multivariable Cox proportional hazard regression models-adjusted for baseline EAT values, age, sex, race, ethnicity, smoking, pack-years, heart disease or myocardial infarction, stroke, hypertension, diabetes, education status, body mass index, and coronary artery calcium-were performed. Results Among 20 661 participants (mean age, 61.4 years ± 5.0 [SD]; 12 237 male [59.2%]), 3483 (16.9%) died over a median follow-up of 10.4 years (IQR, 9.9-10.8 years) (cardiovascular related: 816 [23.4%]; lung cancer related: 705 [20.2%]). Mean EAT volume increased (2.5 cm 3 /m 2 ± 11.0) and density decreased (decrease of 0.5 HU ± 3.0) over 2 years. Atypical changes in EAT volume were independent predictors of all-cause mortality (atypical increase: hazard ratio [HR], 1.15 [95% CI: 1.06, 1.25] [ P < .001]; atypical decrease: HR, 1.34 [95% CI: 1.23, 1.46] [ P < .001]). An atypical decrease in EAT volume was associated with cardiovascular mortality (HR, 1.27 [95% CI: 1.06, 1.51]; P = .009). EAT density increase was associated with all-cause, cardiovascular, and lung cancer mortality (HR, 1.29 [95% CI: 1.18, 1.40] [ P < .001]; HR, 1.29 [95% CI: 1.08, 1.54] [ P = .005]; HR, 1.30 [95% CI: 1.07, 1.57] [ P = .007], respectively). Conclusion EAT volume increase and decrease and EAT density increase beyond typical on subsequent chest CT scans were associated with all-cause mortality in participants screened for lung cancer. EAT volume decrease and EAT density increase were associated with elevated risk of cardiovascular mortality after adjustment for baseline EAT values. © RSNA, 2025 Supplemental material is available for this article. See also the editorial by Fuss in this issue.

Purpose: Due to the increasing number of COVID-19 infections since spring 2020 the patient care workflow underwent changes in Germany. To minimize face-to-face exposure and reduce infection risk, non-time-critical elective medical procedures were postponed. Since ultrasound examinations include non-time-critical elective examinations and often can be substituted by other imaging modalities not requiring direct patient contact, the number of examinations has declined significantly. The aim of this study is to quantify the baseline number of ultrasound examinations in the years before, during, and in the early post-pandemic period of the COVID-19 pandemic (since January 2015 to September 2023), and to measure the number of examinations at different German university hospitals., Materials and Methods: The number of examinations was assessed based on a web-based database at all participating clinics at the indicated time points., Results: N = 288 562 sonographic examinations from four sites were included in the present investigation. From January 2020 to June 2020, a significantly lower number of examinations of n = 591.21 vs. 698.43 (p = 0.01) per month and included center was performed. Also, excluding the initial pandemic period until June 2020, significantly fewer ultrasound examinations were performed compared to pre-pandemic years 648.1 vs. 698.4 (p < 0.05), per month and included center, while here differences between the individual centers were observed. In the late phase of the pandemic (n = 681.96) and in the post-pandemic phase (as defined by the WHO criteria from May 2023; n = 739.95), the number of sonographic examinations returned to pre-pandemic levels., Conclusion: The decline in the number of sonographic examinations caused by the COVID-19 pandemic was initially largely intentional and can be illustrated quantitatively. After an initial abrupt decline in sonographic examinations, the pre-pandemic levels could not be reached for a long time, which could be due to restructuring of patient care and follow-up treatment. In the post-pandemic phase, the pre-pandemic level has been achieved again. The reasons for a prolonged reduction in ultrasound examinations are discussed in this article., Key Points: · During the pandemic, significantly fewer ultrasound examinations were performed in the included centers.. · The number of examinations could not be reach the pre-pandemic level for a long time, which could be due to restructuring of patient care and follow-up treatment.. · Identifying causes for sonographic exam reduction is crucial in pandemic preparedness to uphold healthcare quality and continuity for all patients.. · The prolonged decline in sonographic examinations during the pandemic does not represent a lasting trend, as evidenced by the return to pre-pandemic levels.., Citation Format: · Kottlors J, Fervers P, Froelich M et al. The worldwide COVID-19 pandemic caused a decline in sonographic examinations - is this a continuing trend?. Fortschr Röntgenstr 2024; 196: 1246 - 1252., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Purpose: To evaluate Relaxation-Enhanced Angiography without Contrast and Triggering (REACT), a novel 3D isotropic flow-independent non-contrast-enhanced magnetic resonance angiography (non-CE-MRA) for imaging of the abdominal arteries, by comparing image quality and assessment of vessel stenosis intraindidually with 4D CE-MRA., Methods: Thirty patients (mean age 35.7 ± 16.8 years; 20 females) referred for the assessment of the arterial abdominal vasculature at 3 T were included in this retrospective, single-centre study. The protocol comprised both 4D CE-MRA and REACT (navigator-triggering, Compressed SENSE factor 10, nominal scan time 02:54 min, and reconstructed voxel size 0.78 × 0.78 × 0.85  mm 3 ). Two radiologists independently evaluated 14 abdominal artery segments for stenoses, anatomical variants, and vascular findings (aortic dissection, abdominal aorta aneurysms and its branches). Subjective image quality was assessed using a 4-point Likert scale (1 = non-diagnostic, 4 = excellent)., Results: REACT had a total acquisition time of 5:36 ± 00:40 min, while 4D CE-MRA showed a total acquisition time (including the native scan and bolus tracking sequence) of 3:45 ± 00:59 min (p = 0.001). Considering 4D CE-MRA as the reference standard, REACT achieved a sensitivity of 87.5% and specificity of 100.0% for relevant (≥ 50%) stenosis while detecting 89.5% of all vascular findings other than stenosis. For all vessels combined, subjective vessel quality was slightly higher in 4D CE-MRA (3.0 [IQR: 2.0; 4.0.]; P = 0.040), although comparable to REACT (3.0 [IQR: 2.0; 3.5])., Conclusion: In a short scan time of about 5 min, REACT provides good diagnostic performance for detection of relevant stenoses, variants, and vascular findings of the abdominal arteries, while yielding to 4D CE-MRA comparable image quality., (© 2024. The Author(s).)

Objectives: Coronary CT angiography (CCTA) is becoming increasingly important in the workup of coronary artery disease. Imaging of stents and in-stent stenoses remains a challenge. This work investigates the assessability of in-stent stenoses in photon counting CT (PCCT) using ultra-high-resolution (UHR) imaging and optimized reconstruction kernels., Methods: In an established phantom, 6 stents with inserted hypodense stenoses were scanned in both standard resolution (SRM) and UHR in a clinical PCCT scanner (NAEOTOM Alpha, Siemens Healthineers, Germany). Reconstructions were made both with the clinically established and optimized kernels. The visible stent lumen and the extent of stenosis were quantitatively measured and compared with the angiographic reference standard. Also, region-of-interest (ROI)-based measurements and a qualitative assessment of image quality were performed., Results: The visible stent lumen and the extent of stenosis were measured more precisely in UHR compared to SRM (0.11 ± 0.19 vs 0.41 ± 0.22 mm, P  < .001). The optimized kernel further improved the accuracy of the measurements and image quality in UHR (0.35 ± 0.23 vs 0.47 ± 0.19 mm, P  < .001). Compared to angiography, stenoses were overestimated in PCCT, on average with an absolute difference of 18.20% ± 4.11%., Conclusions: Photon counting CCTA allows improved imaging of in-stent stenoses in a phantom using UHR imaging and optimized kernels. These results support the use of UHR and optimized kernels in clinical practice and further studies., Advances in Knowledge: UHR imaging and optimized reconstruction kernels should be used in CCTA in the presence of cardiac stents., Competing Interests: J.R.K. received honoraria for scientific lectures from GE Healthcare and honoraria for clinical advisory board membership from Siemens Healthineers. J.B. received honoraria for scientific lectures from Siemens Healthineers and Philips Healthcare. B.S., C.P., and M.B.-B. are employees of Siemens Healthineers. R.J.G. received research support from Philips Healthcare and is member on speaker’s bureau of Philips Healthcare., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Institute of Radiology.)

Anecdotal evidence from preliminary observations has noted multiple instances where osteoporosis is present in elderly patients before the clinical detection of bowel disease, even in the absence of overt gastrointestinal symptoms. However, any potential association between these conditions remains to be further investigated. This computed tomography (CT) study investigates whether patients with gastrointestinal (GI) perforation have lower bone mineral density (BMD) than age and sex matched controls. BMD was measured by drawing 3D regions of interest in the bone marrow of the L1-L3 vertebral bodies on CT scans of each of 37 GI perforations and matched controls. Spectrometric calibration of Hounsfield units to the mineral scale was performed with density measurements in the paravertebral muscles (erector spinae) and subcutaneous adipose tissue. The mean BMD of patients with GI perforation (135.9 ± 24.3 mg/ml) was significantly lower than that of controls (96.9 ± 27.5 mg/ml, p < 0.05). The calculated T-and Z-scores of bone mineral density were also significantly different between the two groups (p < 0.05 for each) and were - 2.9 (± 0.90) and - 0.8 (± 0.91) in patients with GI perforation and - 1.6 (± 0.83) and 0 (± 0.96) in the control group, respectively. The results imply that patients with gastrointestinal (GI) perforation have lower bone mineral density (BMD) than age-and sex-matched controls, posing the question whether the screening and aggressive management of osteoporosis is high-risk populations for gastrointestinal perforation can prevent gastrointestinal complications in targeted populations., (© 2024. The Author(s).)

Objectives: To compare immune response evaluation criteria in solid tumors (iRECIST) and response evaluation criteria in solid tumors (RECIST) 1.1 for response assessment of immune checkpoint inhibitor (ICI) therapy in a real-world setting in patients with melanoma and non-small cell lung cancer (NSCLC)., Methods: Two-hundred fifty-two patients with melanoma and NSCLC who received CTLA-4 inhibitor ipilimumab or PD-1 inhibitors nivolumab or pembrolizumab and who underwent staging CT of the chest and abdomen were retrospectively included. Treatment response evaluation according to the RECIST 1.1 and iRECIST guidelines was performed for all patients. Response patterns, as well as overall response rate (ORR), disease control rate (DCR), and time to progression (TTP), were compared between RECIST 1.1 and iRECIST., Results: Out of 143 patients with progressive disease (PD) according to RECIST 1.1, 48 (33.6%) did not attain confirmation of progression (iCPD) as per iRECIST and six patients who were treated beyond RECIST 1.1 progression reached PD at a later point in time in iRECIST, resulting in a significant difference in TTP between iRECIST and RECIST 1.1 (618.3 ± 626.9 days vs. 538.1 ± 617.9 days, respectively (p < 0.05)). The number of non-responders as per RECIST 1.1 was 79, whereas it was 60 when using iRECIST. ORR was 28.5% for RECIST 1.1 and 34.1% for iRECIST, and corresponding DCR of 67.4% for RECIST 1.1 and 74.6% for iRECIST., Conclusion: iRECIST was more suitable than RECIST 1.1 for capturing atypical response patterns to ICI therapy in patients with melanoma and NSCLC, resulting in differences in the assessment of treatment response., Clinical Relevance Statement: Compared to RECIST 1.1, iRECIST may improve patient care and treatment decisions for patients with NSCLC or melanoma who are treated with immune checkpoint inhibitors in clinical routine., Key Points: RECIST 1.1 may incorrectly assess atypical treatment patterns to immune checkpoint inhibitors. iRECIST better captured atypical response patterns compared to RECIST 1.1. iRECIST was more suitable for assessing response to immune checkpoint inhibitors in non-small cell lung carcinoma and melanoma., (© 2024. The Author(s).)

Background: Fibromas are rare primary benign cardiac tumours that can become symptomatic due to expansive growth, ventricular rhythm disturbances, and sudden cardiac death. Distinguishing fibromas from other (malign) cardiac masses is essential for accurate diagnosis and treatment. While there is some experience in management of cardiac fibromas in children, management of adult patients is unknown., Case Summary: We present three cases of cardiac fibroma in adult patients diagnosed by echocardiography, cardiovascular magnetic resonance (CMR), and computed tomography (CT): (1) a 55-year-old male with a left ventricular fibroma leading to reduced left ventricular ejection fraction and mitral regurgitation. He had family history of sudden cardiac death, showed premature ventricular contractions (PVCs), and was treated with a primary preventive subcutaneous implantable cardiac defibrillator (S-ICD); (2) a 39-year-old male with right ventricular fibroma as an incidental finding. He complained of episodes of PVC. Due to a low PVC burden, decision was made against ablation and the patient was planned for follow-up; and (3) an 18-year-old female with left ventricular apex fibroma detected by CMR shortly after birth and confirmed by surgical biopsy. Being asymptomatic, conservative management was pursued and follow-up by CMR planned., Discussion: Cardiac fibromas can show various clinical presentations and hence being detected late in life. Given potential complications of surgical biopsy, diagnosis of cardiac fibromas is primarily based on echocardiography, CT, and CMR. Rhythm disturbances as PVCs are common. Due to association with ventricular arrhythmias and sudden cardiac death, preventive ICD placement might be appropriate on an individual basis., Competing Interests: Conflict of interest: D.M.: speaker’s bureau, Philips Healthcare. L.P.: speaker’s bureau, Philips Healthcare; speaker’s bureau, Guerbet GmbH. The remaining authors disclose no relevant relationships., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background: Coronary artery disease (CAD) and severe aortic valve stenosis (AS) frequently coexist. While pre-transcatheter aortic valve replacement (TAVR) computed tomography angiography (CTA) allows to rule out obstructive CAD, interpreting hemodynamic significance of intermediate stenoses is challenging. This study investigates the incremental value of CT-derived fractional flow reserve (CT-FFR), quantitative coronary plaque characteristics (e.g., stenosis degree, plaque volume, and composition), and peri-coronary adipose tissue (PCAT) density to detect hemodynamically significant lesions among those with AS and CAD., Materials and Methods: We included patients with severe AS and intermediate coronary lesions (20-80% diameter stenosis) who underwent pre-TAVR CTA and invasive coronary angiogram (ICA) with resting full-cycle ratio (RFR) assessment between 08/16 and 04/22. CTA image analysis included assessment of CT-FFR, quantitative coronary plaque analysis, and PCAT density. Coronary lesions with RFR ≤ 0.89 indicated hemodynamic significance as reference standard., Results: Overall, 87 patients (age 77.9 ± 7.4 years, 38% female) with 95 intermediate coronary artery lesions were included. CT-FFR showed good discriminatory capacity (area under receiver operator curve (AUC) = 0.89, 95% confidence interval (CI) 0.81-0.96, p < 0.001) to identify hemodynamically significant lesions, superior to anatomical assessment, plaque morphology, and PCAT density. Plaque composition and PCAT density did not differ between lesions with and without hemodynamic significance. Univariable and multivariable analyses revealed CT-FFR as the only predictor for functionally significant lesions (odds ratio 1.28 (95% CI 1.17-1.43), p < 0.001). Overall, CT-FFR ≤ 0.80 showed diagnostic accuracy, sensitivity, and specificity of 88.4% (95%CI 80.2-94.1), 78.5% (95%CI 63.2-89.7), and 96.2% (95%CI 87.0-99.5), respectively., Conclusion: CT-FFR was superior to CT anatomical, plaque morphology, and PCAT assessment to detect functionally significant stenoses in patients with severe AS., Clinical Relevance Statement: CT-derived fractional flow reserve in patients with severe aortic valve stenosis may be a useful tool for non-invasive hemodynamic assessment of intermediate coronary lesions, while CT anatomical, plaque morphology, and peri-coronary adipose tissue assessment have no incremental or additional benefit. These findings might help to reduce pre-transcatheter aortic valve replacement invasive coronary angiogram., Key Points: • Interpreting the hemodynamic significance of intermediate coronary stenoses is challenging in pre-transcatheter aortic valve replacement CT. • CT-derived fractional flow reserve (CT-FFR) has a good discriminatory capacity in the identification of hemodynamically significant coronary lesions. • CT-derived anatomical, plaque morphology, and peri-coronary adipose tissue assessment did not improve the diagnostic capability of CT-FFR in the hemodynamic assessment of intermediate coronary stenoses., (© 2024. The Author(s).)

Background: To investigate the feasibility of the large language model (LLM) ChatGPT for classifying liver lesions according to the Liver Imaging Reporting and Data System (LI-RADS) based on MRI reports, and to compare classification performance on structured vs. unstructured reports., Methods: LI-RADS classifiable liver lesions were included from German written structured and unstructured MRI reports with report of size, location, and arterial phase contrast enhancement as minimum inclusion requirements. The findings sections of the reports were propagated to ChatGPT (GPT-3.5), which was instructed to determine LI-RADS scores for each classifiable liver lesion. Ground truth was established by two radiologists in consensus. Agreement between ground truth and ChatGPT was assessed with Cohen's kappa. Test-retest reliability was assessed by passing a subset of n  = 50 lesions five times to ChatGPT, using the intraclass correlation coefficient (ICC)., Results: 205 MRIs from 150 patients were included. The accuracy of ChatGPT at determining LI-RADS categories was poor (53% and 44% on unstructured and structured reports). The agreement to the ground truth was higher ( k  = 0.51 and k  = 0.44), the mean absolute error in LI-RADS scores was lower (0.5 ± 0.5 vs. 0.6 ± 0.7, p  < 0.05), and the test-retest reliability was higher (ICC = 0.81 vs. 0.50), in free-text compared to structured reports, respectively, although structured reports comprised the minimum required imaging features significantly more frequently (Chi-square test, p  < 0.05)., Conclusions: ChatGPT attained only low accuracy when asked to determine LI-RADS scores from liver imaging reports. The superior accuracy and consistency throughout free-text reports might relate to ChatGPT's training process., Clinical Relevance Statement: Our study indicates both the necessity of optimization of LLMs for structured clinical data input and the potential of LLMs for creating machine-readable labels based on large free-text radiological databases., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Fervers, Hahnfeldt, Kottlors, Wagner, Maintz, Pinto dos Santos, Lennartz and Persigehl.)

Purpose: To investigate the potential of combining Compressed Sensing (CS) and a newly developed AI-based super resolution reconstruction prototype consisting of a series of convolutional neural networks (CNN) for a complete five-minute 2D knee MRI protocol., Methods: In this prospective study, 20 volunteers were examined using a 3T-MRI-scanner (Ingenia Elition X, Philips). Similar to clinical practice, the protocol consists of a fat-saturated 2D-proton-density-sequence in coronal, sagittal and transversal orientation as well as a sagittal T1-weighted sequence. The sequences were acquired with two different resolutions (standard and low resolution) and the raw data reconstructed with two different reconstruction algorithms: a conventional Compressed SENSE (CS) and a new CNN-based algorithm for denoising and subsequently to interpolate and therewith increase the sharpness of the image (CS-SuperRes). Subjective image quality was evaluated by two blinded radiologists reviewing 8 criteria on a 5-point Likert scale and signal-to-noise ratio calculated as an objective parameter., Results: The protocol reconstructed with CS-SuperRes received higher ratings than the time-equivalent CS reconstructions, statistically significant especially for low resolution acquisitions (e.g., overall image impression: 4.3 ± 0.4 vs. 3.4 ± 0.4, p < 0.05). CS-SuperRes reconstructions for the low resolution acquisition were comparable to traditional CS reconstructions with standard resolution for all parameters, achieving a scan time reduction from 11:01 min to 4:46 min (57 %) for the complete protocol (e.g. overall image impression: 4.3 ± 0.4 vs. 4.0 ± 0.5, p < 0.05)., Conclusion: The newly-developed AI-based reconstruction algorithm CS-SuperRes allows to reduce scan time by 57% while maintaining unchanged image quality compared to the conventional CS reconstruction., Competing Interests: Declaration of competing interest David Maintz is part of the speakers bureau at Philips Healthcare; all other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Introduction: This study investigated the use of dual-energy spectral detector computed tomography (CT) and virtual monoenergetic imaging (VMI) reconstructions in pre-interventional transcatheter aortic valve replacement (TAVR) planning. We aimed to determine the minimum required contrast medium (CM) amount to maintain diagnostic CT imaging quality for TAVR planning., Methods: In this prospective clinical trial, TAVR candidates received a standardized dual-layer spectral detector CT protocol. The CM amount (Iohexol 350 mg iodine/mL, standardized flow rate 3 mL/s) was reduced systematically after 15 patients by 10 mL, starting at 60 mL (institutional standard). We evaluated standard, and 40- and 60-keV VMI reconstructions. For image quality, we measured signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and diameters in multiple vessel sections (i.e., aortic annulus: diameter, perimeter, area; aorta/arteries: minimal diameter). Mixed regression models (MRM), including interaction terms and clinical characteristics, were used for comparison., Results: Sixty consecutive patients (mean age, 79.4 ± 7.5 years; 28 females, 46.7%) were included. In pre-TAVR CT, the CM reduction to 40 mL is possible without affecting the image quality (MRM: SNR: -1.1, p = 0.726; CNR: 0.0, p = 0.999). VMI 40-keV reconstructions showed better results than standard reconstructions with significantly higher SNR (+ 6.04, p < 0.001). Reduction to 30 mL CM resulted in a significant loss of quality (MRM: SNR: -12.9, p < 0.001; CNR: -13.9, p < 0.001), regardless of the reconstruction. Across the reconstructions, we observed no differences in the metric evaluation (p > 0.914)., Conclusion: Among TAVR candidates undergoing pre-interventional CT at a dual-layer spectral detector system, applying 40 mL CM is sufficient to maintain diagnostic image quality. VMI 40-keV reconstructions improve the vessel attenuation and are recommended for evaluation., Clinical Relevance Statement: Contrast medium reduction to 40 mL in pre-interventional transcatheter aortic valve replacement CT using dual-energy CT maintains image quality, while 40-keV virtual monoenergetic imaging reconstructions enhance vessel attenuation. These results offer valuable recommendations for interventional transcatheter aortic valve replacement evaluation and potentially improve nephroprotection in patients with compromised renal function., Key Points: • Patients undergoing transcatheter aortic valve replacement (TAVR), requiring pre-interventional CT, are often multimorbid with impaired renal function. • Using a spectral detector dual-layer CT, contrast medium reduction to 40 mL is feasible, maintaining diagnostic image quality. • The additional application of virtual monoenergetic image reconstructions with 40 keV improves vessel attenuation significantly in clinical practice., (© 2023. The Author(s).)

Objectives: To evaluate dual-layer dual-energy computed tomography (dlDECT)-derived pulmonary perfusion maps for differentiation between acute pulmonary embolism (PE) and chronic thromboembolic pulmonary hypertension (CTEPH)., Methods: This retrospective study included 131 patients (57 patients with acute PE, 52 CTEPH, 22 controls), who underwent CT pulmonary angiography on a dlDECT. Normal and malperfused areas of lung parenchyma were semiautomatically contoured using iodine density overlay (IDO) maps. First-order histogram features of normal and malperfused lung tissue were extracted. Iodine density (ID) was normalized to the mean pulmonary artery (MPA) and the left atrium (LA). Furthermore, morphological imaging features for both acute and chronic PE, as well as the combination of histogram and morphological imaging features, were evaluated., Results: In acute PE, normal perfused lung areas showed a higher mean and peak iodine uptake normalized to the MPA than in CTEPH (both p < 0.001). After normalizing mean ID in perfusion defects to the LA, patients with acute PE had a reduced average perfusion (ID mean,LA ) compared to both CTEPH patients and controls (p < 0.001 for both). ID mean,LA allowed for a differentiation between acute PE and CTEPH with moderate accuracy (AUC: 0.72, sensitivity 74%, specificity 64%), resulting in a PPV and NPV for CTEPH of 64% and 70%. Combining ID mean,LA in the malperfused areas with the diameter of the MPA (MPA dia ) significantly increased its ability to differentiate between acute PE and CTEPH (sole MPA dia : AUC: 0.76, 95%-CI: 0.68-0.85 vs. MPA dia + 256.3 * ID mean,LA - 40.0: AUC: 0.82, 95%-CI: 0.74-0.90, p = 0.04)., Conclusion: dlDECT enables quantification and characterization of pulmonary perfusion patterns in acute PE and CTEPH. Although these lack precision when used as a standalone criterion, when combined with morphological CT parameters, they hold potential to enhance differentiation between the two diseases., Clinical Relevance Statement: Differentiating between acute PE and CTEPH based on morphological CT parameters is challenging, often leading to a delay in CTEPH diagnosis. By revealing distinct pulmonary perfusion patterns in both entities, dlDECT may facilitate timely diagnosis of CTEPH, ultimately improving clinical management., Key Points: • Morphological imaging parameters derived from CT pulmonary angiography to distinguish between acute pulmonary embolism and chronic thromboembolic pulmonary hypertension lack diagnostic accuracy. • Dual-layer dual-energy CT reveals different pulmonary perfusion patterns between acute pulmonary embolism and chronic thromboembolic pulmonary hypertension. • The identified parameters yield potential to enable more timely identification of patients with chronic thromboembolic pulmonary hypertension., (© 2023. The Author(s).)

Background: To investigate the potential of combining compressed sensing (CS) and artificial intelligence (AI), in particular deep learning (DL), for accelerating three-dimensional (3D) magnetic resonance imaging (MRI) sequences of the knee., Methods: Twenty healthy volunteers were examined using a 3-T scanner with a fat-saturated 3D proton density sequence with four different acceleration levels (10, 13, 15, and 17). All sequences were accelerated with CS and reconstructed using the conventional and a new DL-based algorithm (CS-AI). Subjective image quality was evaluated by two blinded readers using seven criteria on a 5-point-Likert-scale (overall impression, artifacts, delineation of the anterior cruciate ligament, posterior cruciate ligament, menisci, cartilage, and bone). Using mixed models, all CS-AI sequences were compared to the clinical standard (sense sequence with an acceleration factor of 2) and CS sequences with the same acceleration factor., Results: 3D sequences reconstructed with CS-AI achieved significantly better values for subjective image quality compared to sequences reconstructed with CS with the same acceleration factor (p ≤ 0.001). The images reconstructed with CS-AI showed that tenfold acceleration may be feasible without significant loss of quality when compared to the reference sequence (p ≥ 0.999)., Conclusions: For 3-T 3D-MRI of the knee, a DL-based algorithm allowed for additional acceleration of acquisition times compared to the conventional approach. This study, however, is limited by its small sample size and inclusion of only healthy volunteers, indicating the need for further research with a more diverse and larger sample., Trial Registration: DRKS00024156., Relevance Statement: Using a DL-based algorithm, 54% faster image acquisition (178 s versus 384 s) for 3D-sequences may be possible for 3-T MRI of the knee., Key Points: • Combination of compressed sensing and DL improved image quality and allows for significant acceleration of 3D knee MRI. • DL-based algorithm achieved better subjective image quality than conventional compressed sensing. • For 3D knee MRI at 3 T, 54% faster image acquisition may be possible., (© 2024. The Author(s).)

Introduction: In esophageal cancer, histopathologic response following neoadjuvant therapy and transthoracic esophagectomy is a strong predictor of long-term survival. At the present, it is not known whether the initial tumor volume quantified by computed tomography (CT) correlates with the degree of pathologic regression., Methods: In a retrospective analysis of a consecutive patient cohort with esophageal adenocarcinoma, tumor volume in CT prior to chemoradiotherapy or chemotherapy alone was quantified using manual segmentation. Primary tumor volume was correlated to the histomorphological regression based on vital residual tumor cells (VRTC) (Cologne regression scale, CRS: grade I, >50% VRTC; grade II, 10-50% VRTC; grade III, <10% VRTC and grade IV, complete response without VRTC)., Results: A total of 287 patients, 165 with neoadjuvant chemoradiotherapy according to the CROSS protocol and 122 with chemotherapy according to the FLOT regimen, were included. The initial tumor volume for patients following CROSS and FLOT therapy was measured (CROSS: median 24.8 ml, IQR 13.1-41.1 ml, FLOT: 23.4 ml, IQR 10.6-37.3 ml). All patients underwent an Ivor-Lewis esophagectomy. 180 patients (62.7 %) were classified as minor (CRS I/II) and 107 patients (37.3 %) as major or complete responder (CRS III/IV). The median tumor volume was calculated as 24.2 ml (IQR 11.9-40.3 ml). Ordered logistic regression revealed no significant dependence of CRS from tumor volume (OR = 0.99, p-value = 0.99) irrespective of the type of multimodal treatment., Conclusion: The initial tumor volume on diagnostic CT does not aid to differentiate between potential histopathological responders and non-responders to neoadjuvant therapy in esophageal cancer patients. The results emphasize the need to establish other biological markers of prediction., Competing Interests: Declaration of competing interest There is no conflict of interest regarding our manuscript., (© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

Background Errors in radiology reports may occur because of resident-to-attending discrepancies, speech recognition inaccuracies, and large workload. Large language models, such as GPT-4 (ChatGPT; OpenAI), may assist in generating reports. Purpose To assess effectiveness of GPT-4 in identifying common errors in radiology reports, focusing on performance, time, and cost-efficiency. Materials and Methods In this retrospective study, 200 radiology reports (radiography and cross-sectional imaging [CT and MRI]) were compiled between June 2023 and December 2023 at one institution. There were 150 errors from five common error categories (omission, insertion, spelling, side confusion, and other) intentionally inserted into 100 of the reports and used as the reference standard. Six radiologists (two senior radiologists, two attending physicians, and two residents) and GPT-4 were tasked with detecting these errors. Overall error detection performance, error detection in the five error categories, and reading time were assessed using Wald χ 2 tests and paired-sample t tests. Results GPT-4 (detection rate, 82.7%;124 of 150; 95% CI: 75.8, 87.9) matched the average detection performance of radiologists independent of their experience (senior radiologists, 89.3% [134 of 150; 95% CI: 83.4, 93.3]; attending physicians, 80.0% [120 of 150; 95% CI: 72.9, 85.6]; residents, 80.0% [120 of 150; 95% CI: 72.9, 85.6]; P value range, .522-.99). One senior radiologist outperformed GPT-4 (detection rate, 94.7%; 142 of 150; 95% CI: 89.8, 97.3; P = .006). GPT-4 required less processing time per radiology report than the fastest human reader in the study (mean reading time, 3.5 seconds ± 0.5 [SD] vs 25.1 seconds ± 20.1, respectively; P < .001; Cohen d = -1.08). The use of GPT-4 resulted in lower mean correction cost per report than the most cost-efficient radiologist ($0.03 ± 0.01 vs $0.42 ± 0.41; P < .001; Cohen d = -1.12). Conclusion The radiology report error detection rate of GPT-4 was comparable with that of radiologists, potentially reducing work hours and cost. © RSNA, 2024 See also the editorial by Forman in this issue.

Rationale and Objectives: Coronary computed tomography angiography (CCTA) is becoming increasingly important for the diagnostic workup of coronary artery disease, nevertheless, imaging of in-stent stenosis remains challenging. For the first time, spectral imaging in Ultra High Resolution (UHR) is now possible in clinically available photon counting CT. The aim of this work is to determine the optimal virtual monoenergetic image (VMI) for imaging in-stent stenoses in cardiac stents., Materials and Methods: 6 stents with inserted hypodense stenoses were scanned in an established phantom in UHR mode. Images were reconstructed with 3 different kernels for spectral data (Qr56, Qr64, Qr72) with varying levels of sharpness. Based on region of interest (ROI) measurements image quality parameters including contrast-to-noise ratio (CNR) were analyzed for all available VMI (40 keV-190 keV). Finally, based on quantitative results and VMI used in clinical routine, a set of VMI was included in a qualitative reading., Results: CNR showed significant variations across different keV levels (p < 0.001). Due to reduced noise there was a focal maximum in the VMI around 65 keV. The peak values were observed for kernel Qr56 at 116 keV with 19.47 ± 8.67, for kernel Qr64 at 114 keV with 13.56 ± 6.58, and for kernel Qr72 at 106 keV with 12.19 ± 3.25. However, in the qualitative evaluation the VMI with lower keV (55 keV) performed best., Conclusions: Based on these experimental results, a photon counting CCTA in UHR with stents should be reconstructed with the Qr72 kernel for the assessment of in-stent stenoses, and a VMI 55 keV should be computed for the evaluation., Competing Interests: J. R. Kroeger received honoraria for scientific lectures from GE Healthcare and honoraria for clinical advisory board membership from Siemens Healthineers. J. Borggrefe received honoraria for scientific lectures from Siemens Healthineers and Philips Healthcare. B. Schmidt and Ch. Panknin are empoyees of Siemens Healthineers. R. J. Gertz is supported by the Cologne Clinician Scientist Program (CCSP)/Faculty of Medicine/10.13039/501100008001University of Cologne, funded by the 10.13039/501100001659Deutsche Forschungsgemeinschaft (10.13039/501100001659DFG, German Research Foundation) (Project No. 413543196), received research support from 10.13039/100004320Philips Healthcare and is member on speaker's bureau of 10.13039/100004320Philips Healthcare., (© 2024 The Author(s).)

Objective: We aimed to asses, in a clinical setting, whether the newly available quantitative evaluation of electron density (ED) in spectral CT examinations of the breast provide information on the biological identity of solid breast masses and whether ED maps yield added value to the diagnostic information of iodine maps and Zeff maps calculated from the same CT image datasets., Methods: All patients at the University Breast Cancer Center who underwent a clinically indicated Dual Layer Computed Tomography (DLCT) examination for staging of invasive breast cancer from 2018 to 2020 were prospectively included. Iodine concentration maps, Zeff maps and ED maps were automatically reconstructed from the DLCT datasets. Region of interest (ROI) based evaluations in the breast target lesions and in the aorta were performed semi-automatically in identical anatomical positions using dedicated evaluation software. Case-by-case evaluations were carried independently by 2 of 4 radiologists for each examination, respectively. Statistical analysis derived from the ROIs was done by calculating ROC/AUC curves and Youden indices., Results: The evaluations comprised 166 DLCT examinations. In the ED maps the measurements in the breast target lesions yielded Youden cutpoints of 104.0% (reader 1) and 103.8% (reader 2) resulting in AUCs of 0.63 and 0.67 at the empirical cutpoints. The variables "Zeff" and "iodine content" derived from the target lesions showed superior diagnostical results, with a Youden cutpoint of 8.0 mg/ml in the iodine maps and cutpoints of 1.1/1.2 in the Zeff maps the AUCs ranging from 0.84 to 0.85 (p = 0.023 to <0.000). The computational combination of Zeff and ED measurements in the target lesions yielded a slight AUC increase (readers 1: 0.85-0.87; readers 2: 0.84-0.94). The ratios of the measured values in the target lesions normalized to the values measured in the aorta showed comparable results. The AUCs of ED derived from the cutpoints showed inferior results to those derived from the Zeff maps and iodine maps (ED: 0.64 and 0.66 for reader 1 and 2; Zeff: 0.86 for both readers; iodine content: 0.89 and 0.86 for reader 1 and 2, respectively). The computational combination of the ED results and the Zeff measurements did not lead to a clinically relevant diagnostic gain with AUCs ranging from 0.86 to 0.88., Conclusions: Quantitative assessments of Zeff, iodine content and ED all targeting the physical and chemical aspects of iodine uptake in solid breast masses confirmed diagnostically robust cutpoints for the differentiation of benign and malignant findings (Zeff < 7.7, iodine content of <0.8 mg/ml). The evaluations of the ED did not indicate any added diagnostic value beyond the quantitative assessments of Zeff and iodine content. Further research is warranted to develop suitable clinical indications for the use of ED maps., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Diagnosing myocarditis relies on multimodal data, including cardiovascular magnetic resonance (CMR), clinical symptoms, and blood values. The correct interpretation and integration of CMR findings require radiological expertise and knowledge. We aimed to investigate the performance of Generative Pre-trained Transformer 4 (GPT-4), a large language model, for report-based medical decision-making in the context of cardiac MRI for suspected myocarditis., Methods: This retrospective study includes CMR reports from 396 patients with suspected myocarditis and eight centers, respectively. CMR reports and patient data including blood values, age, and further clinical information were provided to GPT-4 and radiologists with 1 (resident 1), 2 (resident 2), and 4 years (resident 3) of experience in CMR and knowledge of the 2018 Lake Louise Criteria. The final impression of the report regarding the radiological assessment of whether myocarditis is present or not was not provided. The performance of Generative pre-trained transformer 4 (GPT-4) and the human readers were compared to a consensus reading (two board-certified radiologists with 8 and 10 years of experience in CMR). Sensitivity, specificity, and accuracy were calculated., Results: GPT-4 yielded an accuracy of 83%, sensitivity of 90%, and specificity of 78%, which was comparable to the physician with 1 year of experience (R1: 86%, 90%, 84%, p = 0.14) and lower than that of more experienced physicians (R2: 89%, 86%, 91%, p = 0.007 and R3: 91%, 85%, 96%, p < 0.001). GPT-4 and human readers showed a higher diagnostic performance when results from T1- and T2-mapping sequences were part of the reports, for residents 1 and 3 with statistical significance (p = 0.004 and p = 0.02, respectively)., Conclusion: GPT-4 yielded good accuracy for diagnosing myocarditis based on CMR reports in a large dataset from multiple centers and therefore holds the potential to serve as a diagnostic decision-supporting tool in this capacity, particularly for less experienced physicians. Further studies are required to explore the full potential and elucidate educational aspects of the integration of large language models in medical decision-making., Competing Interests: Declaration of competing interests The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: David Maintz received speaker’s honoraria from Philips Healthcare. Jan Borggrefe received speaker’s honoraria from Siemens Healthineers. Simon Lennartz is a member of Editorial Board of Radiology and a Senior Deputy Editor of Radiology in Training. Otherwise, the authors declare no conflicts of interest and had full control over all data, and guarantee correctness., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Percutaneous drainage is a first-line therapy for abscesses and other fluid collections. However, experimental data on the viscosity of body fluids are scarce. This study analyses the apparent viscosity of serous, purulent and biliary fluids to provide reference data for the evaluation of drainage catheters. Serous, purulent and biliary fluid samples were collected during routine drainage procedures. In a first setup, the apparent kinematic viscosity of 50 fluid samples was measured using an Ubbelohde viscometer. In a second setup, the apparent dynamic viscosity of 20 fluid samples obtained during CT-guided percutaneous drainage was measured using an in-house designed capillary extrusion experiment. The median apparent kinematic viscosity was 0.96 mm 2 /s (IQR 0.90-1.15 mm 2 /s) for serous samples, 0.98 mm 2 /s (IQR 0.97-0.99 mm 2 /s) for purulent samples and 2.77 mm 2 /s (IQR 1.75-3.70 mm 2 /s) for biliary samples. The median apparent dynamic viscosity was 1.63 mPa*s (IQR 1.27-2.09 mPa*s) for serous samples, 2.45 mPa*s (IQR 1.69-3.22 mPa*s) for purulent samples and 3.50 mPa*s (IQR 2.81-3.90 mPa*s) for biliary samples (all differences p < 0.01). Relative to water, dynamic viscosities were increased by a factor of 1.36 for serous fluids, 2.26 for purulent fluids, and 4.03 for biliary fluids. Serous fluids have apparent viscosities similar to water, but biliary and purulent fluids are more viscous. These data can be used as a reference when selecting the drainage catheter size, with 8F catheters being appropriate for most percutaneous drainage cases., (© 2023. The Author(s).)

Aim: The purpose of this study was to investigate the clinical application of Compressed SENSE accelerated single-breath-hold LGE with 3D isotropic resolution compared to conventional LGE imaging acquired in multiple breath-holds., Material & Methods: This was a retrospective, single-center study including 105 examinations of 101 patients (48.2 ± 16.8 years, 47 females). All patients underwent conventional breath-hold and 3D single-breath-hold (0.96 × 0.96 × 1.1 mm 3 reconstructed voxel size, Compressed SENSE factor 6.5) LGE sequences at 1.5 T in clinical routine for the evaluation of ischemic or non-ischemic cardiomyopathies. Two radiologists independently evaluated the left ventricle (LV) for the presence of hyperenhancing lesions in each sequence, including localization and transmural extent, while assessing their scar edge sharpness (SES). Confidence of LGE assessment, image quality (IQ), and artifacts were also rated. The impact of LV ejection fraction (LVEF), heart rate, body mass index (BMI), and gender as possible confounders on IQ, artifacts, and confidence of LGE assessment was evaluated employing ordinal logistic regression analysis., Results: Using 3D single-breath-hold LGE readers detected more hyperenhancing lesions compared to conventional breath-hold LGE ( n  = 246 vs. n  = 216 of 1,785 analyzed segments, 13.8% vs. 12.1%; p  < 0.0001), pronounced at subendocardial, midmyocardial, and subepicardial localizations and for 1%-50% of transmural extent. SES was rated superior in 3D single-breath-hold LGE (4.1 ± 0.8 vs. 3.3 ± 0.8; p  < 0.001). 3D single-breath-hold LGE yielded more artifacts (3.8 ± 1.0 vs. 4.0 ± 3.8; p  = 0.002) whereas IQ (4.1 ± 1.0 vs. 4.2 ± 0.9; p  = 0.122) and confidence of LGE assessment (4.3 ± 0.9 vs. 4.3 ± 0.8; p  = 0.374) were comparable between both techniques. Female gender negatively influenced artifacts in 3D single-breath-hold LGE ( p  = 0.0028) while increased heart rate led to decreased IQ in conventional breath-hold LGE ( p  = 0.0029)., Conclusions: In clinical routine, Compressed SENSE accelerated 3D single-breath-hold LGE yields image quality and confidence of LGE assessment comparable to conventional breath-hold LGE while providing improved delineation of smaller LGE lesions with superior scar edge sharpness. Given the fast acquisition of 3D single-breath-hold LGE, the technique holds potential to drastically reduce the examination time of CMR., Competing Interests: RG: Research support and speakers bureau, Philips Healthcare. Speakers bureau, Guerbet GmbH. JG: Speakers bureau, Siemens Healthineers. DM: Speakers bureau, Philips Healthcare. KW, CK: Employees, Philips Healthcare. LP: Speakers bureau, Philips Healthcare. Speakers bureau, Guerbet GmbH. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Gertz, Wagner, Sokolowski, Lennartz, Gietzen, Grunz, Goertz, Kaya, ten Freyhaus, Persigehl, Bunck, Doerner, Naehle, Maintz, Weiss, Katemann and Pennig.)

Objective: To compare the measurement of aortic diameters using a novel flow-independent MR-Angiography (3D modified Relaxation-Enhanced Angiography without Contrast and Triggering (modified REACT)) and transthoracic echocardiography (TTE) in Marfan syndrome (MFS) patients., Material and Methods: This retrospective, single-center analysis included 46 examinations of 32 MFS patients (mean age 37.5 ± 11.3 years, 17 women, no prior aortic surgery) who received TTE and 3D modified REACT (ECG- and respiratory-triggering, Compressed SENSE factor 9 for acceleration of image acquisition) of the thoracic aorta. Aortic diameters (sinus of Valsalva (SV), sinotubular junction (STJ), and ascending aorta (AoA)) were independently measured by two cardiologists in TTE (leading-edge) and two radiologists in modified REACT (inner-edge, using multiplanar reconstruction). Intraclass correlation coefficient, Bland-Altman analyses, and Pearson's correlation (r) were used to assess agreement between observers and methods., Results: Interobserver correlation at the SV, STJ, and AoA were excellent for both, TTE (ICC = 0.95-0.98) and modified REACT (ICC = 0.99-1.00). There was no significant difference between TTE and modified REACT for diameters measured at the SV (39.24 ± 3.24 mm vs. 39.63 ± 3.76 mm; p = 0.26; r = 0.78) and the STJ (35.16 ± 4.47 mm vs. 35.37 ± 4.74 mm; p = 0.552; r = 0.87). AoA diameters determined by TTE were larger than in modified REACT (34.29 ± 5.31 mm vs. 30.65 ± 5.64 mm; p < 0.01; r = 0.74). The mean scan time of modified REACT was 05:06 min ± 02:47 min, depending on the patient's breathing frequency and heart rate., Conclusions: Both TTE and modified REACT showed a strong correlation for all aortic levels; however, at the AoA, diameters were larger using TTE, mostly due to the limited field of view of the latter with measurements being closer to the aortic valve. Given the excellent interobserver correlation and the strong agreement with TTE, modified REACT represents an attractive method to depict the thoracic aorta in MFS patients., Competing Interests: Declaration of Competing Interest Kilian Weiss: Employee, Philips GmbH. Roman Johannes Gertz: Received research support from Philips Healthcare. David Maintz: Speaker's bureau, Philips Healthcare. Lenhard Pennig: Speaker's bureau, Philips Healthcare. Speaker's bureau, Guerbet GmbH. Henrik ten Freyhaus: Speaker's bureau, Guerbet GmbH, consulting activities, General Electrics. The remaining authors disclose no relevant relationships., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: To investigate the potential of combining compressed sensing (CS) and deep learning (DL) for accelerated two-dimensional (2D) and three-dimensional (3D) magnetic resonance imaging (MRI) of the shoulder., Methods: Twenty healthy volunteers were examined using at 3-T scanner with a fat-saturated, coronal, 2D proton density-weighted sequence with four acceleration levels (2.3, 4, 6, and 8) and a 3D sequence with three acceleration levels (8, 10, and 13), all accelerated with CS and reconstructed using the conventional algorithm and a new DL-based algorithm (CS-AI). Subjective image quality was evaluated by two blinded readers using 6 criteria on a 5-point Likert scale (overall impression, artifacts, and delineation of the subscapularis tendon, bone, acromioclavicular joint, and glenoid labrum). Objective image quality was measured by calculating signal-to-noise-ratio, contrast-to-noise-ratio, and a structural similarity index measure. All reconstructions were compared to the clinical standard (CS 2D acceleration factor 2.3; CS 3D acceleration factor 8). Additionally, subjective and objective image quality were compared between CS and CS-AI with the same acceleration levels., Results: Both 2D and 3D sequences reconstructed with CS-AI achieved on average significantly better subjective and objective image quality compared to sequences reconstructed with CS with the same acceleration factor (p ≤ 0.011). Comparing CS-AI to the reference sequences showed that 4-fold acceleration for 2D sequences and 13-fold acceleration for 3D sequences without significant loss of quality (p ≥ 0.058)., Conclusions: For MRI of the shoulder at 3 T, a DL-based algorithm allowed additional acceleration of acquisition times compared to the conventional approach., Relevance Statement: The combination of deep-learning and compressed sensing hold the potential for further scan time reduction in 2D and 3D imaging of the shoulder while providing overall better objective and subjective image quality compared to the conventional approach., Trial Registration: DRKS00024156., Key Points: • Combination of compressed sensing and deep learning improved image quality and allows for significant acceleration of shoulder MRI. • Deep learning-based algorithm achieved better subjective and objective image quality than conventional compressed sensing. • For shoulder MRI at 3 T, 40% faster image acquisition for 2D sequences and 38% faster image acquisition for 3D sequences may be possible., (© 2023. European Society of Radiology (ESR).)

Purpose: Imaging stents and in-stent stenosis remains a challenge in coronary computed tomography angiography (CCTA). In comparison to conventional Computed Tomography, Photon Counting CT (PCCT) provides decisive clinical advantages, among other things by providing low dose ultra-high resolution imaging of coronary arteries. This work investigates the image quality in CCTA using clinically established kernels and those optimized for the imaging of cardiac stents in PCCT, both for in-vitro stent imaging in 400 μm standard resolution mode (SRM) and 200 μm Ultra High Resolution Mode (UHR)., Methods: Based on experimental scans, vascular reconstruction kernels (Bv56, Bv64, Bv72) were optimized. In an established phantom, 10 different coronary stents with 3 mm diameter were scanned in the first clinically available PCCT. Scans were reconstructed with clinically established and optimized kernels. Four readers measured visible stent lumen, performed ROI-based density measurements and rated image quality., Results: Regarding the visible stent lumen, UHR is significantly superior to SRM (p < 0.001). In all levels, the optimized kernels are superior to the clinically established kernels (p < 0.001). One optimized kernel showed a significant reduction of noise compared to the clinically established kernels. Overall image quality is improved with optimized kernels., Conclusions: In a phantom study PCCT UHR with optimized kernels for stent imaging significantly improves the ability to assess the in-stent lumen of small cardiac stents. We recommend using UHR with an optimized sharp vascular reconstruction kernel (Bv72uo) for imaging of cardiac stent., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [J.R. Kroeger received research support from Philips, support for attending meetings and/or travel from Veryan, honoraria for scientific lectures from GE Healthcare and honoraria for clinical advisory board membership from Siemens Healthineers. J. Borggrefe received honoraria for scientific lectures from Siemens Healthineers and Philips Healthcare. Th. Flohr, B. Schmidt, Ch. Panknin and M. Baer-Beck are empoyees of Siemens Healthineers.]., (Copyright © 2023 Elsevier B.V. All rights reserved.)

This study aimed to compare the image quality and diagnostic accuracy of deep-learning-based image denoising reconstructions (DLIDs) to established iterative reconstructed algorithms in low-dose computed tomography (LDCT) of patients with suspected urolithiasis. LDCTs (CTDIvol, 2 mGy) of 76 patients (age: 40.3 ± 5.2 years, M/W: 51/25) with suspected urolithiasis were retrospectively included. Filtered-back projection (FBP), hybrid iterative and model-based iterative reconstruction (HIR/MBIR, respectively) were reconstructed. FBP images were processed using a Food and Drug Administration (FDA)-approved DLID. ROIs were placed in renal parenchyma, fat, muscle and urinary bladder. Signal- and contrast-to-noise ratios (SNR/CNR, respectively) were calculated. Two radiologists evaluated image quality on five-point Likert scales and urinary stones. The results showed a progressive decrease in image noise from FBP, HIR and DLID to MBIR with significant differences between each method ( p < 0.05). SNR and CNR were comparable between MBIR and DLID, while it was significantly lower in HIR followed by FBP (e.g., SNR: 1.5 ± 0.3; 1.4 ± 0.4; 1.0 ± 0.3; 0.7 ± 0.2, p < 0.05). Subjective analysis confirmed best image quality in MBIR, followed by DLID and HIR, both being superior to FBP ( p < 0.05). Diagnostic accuracy for urinary stone detection was best using MBIR (0.94), lowest using FBP (0.84) and comparable between DLID (0.90) and HIR (0.90). Stone size measurements were consistent between all reconstructions and showed excellent correlation (r 2 = 0.958-0.975). In conclusion, MBIR yielded the highest image quality and diagnostic accuracy, with DLID producing better results than HIR and FBP in image quality and matching HIR in diagnostic precision.

Background: Left atrial outpouching structures such as left atrial diverticula (LADs) and left-sided septal pouches (LSSPs) might be a source of cryptogenic stroke. This imaging study evaluates the association between pouch morphology, patient comorbidities and ischemic brain lesions (IBLs)., Methods: This is a retrospective single-center analysis of 195 patients who received both a cardiac CT and a cerebral MRI. LADs, LSSPs, and IBLs were retrospectively identified. Size measurements included pouch width, length and volume for LADs and circumference, area and volume for LSSPs. The association between LADs/LSSPs, IBLs and cardiovascular comorbidities was determined by univariate and bivariate regression analyses., Results: The prevalence and mean volume were 36.4% and 372 ± 569 mm 3 for LSSPs, and 40.5% and 415 ± 541 mm 3 for LADs. The IBL prevalence was 67.6% in the LSSP group and 48.1% in the LAD group. LSSPs had 2.9-fold increased hazards of IBLs (95%CI: 1.2-7.4, p = 0.024), and LADs showed no significant correlation with IBLs. Size measurements had no impact on IBLs. A co-existing LSSP was associated with an increased prevalence of IBLs in patients with coronary artery disease (HR: 1.5, 95%CI: 1.1-1.9, p = 0.048), heart failure (HR: 3.7, 95%CI: 1.1-14.6, p = 0.032), arterial hypertension (HR: 1.9, 95%CI: 1.1-3.3, p = 0.017), and hyperlipidemia (HR: 2.2, 95%CI: 1.1-4.4, p = 0.018)., Conclusion: Co-existing LSSPs were associated with IBLs in patients with cardiovascular risk factors, however, pouch morphology did not correlate with the IBL rate. Upon confirmation by further studies, these findings might be considered in the treatment, risk stratification, and stroke prophylaxis of these patients., Competing Interests: Declaration of competing interest David Maintz has received speaker's honoraria from Philips Healthcare, unrelated to the presented work. Christoph Kabbasch serves as consultant for Acandis GmbH (Pforzheim, Germany) and as proctor for MicroVention Inc./Sequent Medical (Aliso Viejo, CA, USA), unrelated to the presented work. The other authors declare no conflict of interest., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Objective: To asses the correlation of data derived from dual-layer (DL)-CT material-maps and breast MRI data with molecular biomarkers in invasive breast carcinomas., Methods: All patients at the University Breast Cancer Center who underwent a clinically indicated DLCT-scan and a breast MRI for staging of invasive ductal breast cancer from 2016 to 2020 were prospectively included. Iodine concentration-maps, and Zeffective-maps were reconstructed from the CT-datasets. T1w- and T2w-signal intensities, ADC and the clustered shapes of the dynamic-curves (washout, plateau, persistent) were derived from the MRI-datasets. ROI-based evaluations of the cancers and the reference "musculature" were performed semi-automatically in identical anatomical positions using dedicated evaluation software. Statistical analysis was essentially descriptive using Spearmańs rank correlation and (multivariable) partial correlation., Results: The signal intensities measured in the 3rd phase of the contrast dynamics correlated at an intermediate level of significance with the iodine content and the Zeffective-values derived from the breast target lesions (Spearmańs rank correlation-coefficient r = 0.237/0.236, p = 0.002/0.003). The bivariate and the multivariate analyses displayed correlations of an intermediate significance level of the iodine content and the Zeff-values measured in the breast target lesions with immunhistochemical subtyping (r = 0.211-0.243, p = 0.002-0.009, respectively). The Zeff-values showed the strongest correlations when normalized to the values measured in the musculature and in the aorta (r = -0.237 to -0.305, r=<0.001-0.003). The MRI-assessments showed correlations of intermediate to high significance and low to intermediate significance between the ratios of the T2w-signal intensities and the trends of the dynamic curves measured in the breast target lesions and in musculature and immunohistochemical cancer subtyping, respectively (T2w: r = 0.232-0.249, p = 0.003/0.002; dynamics: r = -0.322/-0.245, p=<0.001/0.002). The ratios of the clustered trends of the dynamic curves measured in the breast target lesions and in musculature correlated with tumor grading on intermediate significance level (r = -0.213 and -0.194, p = 0.007/0.016) and with Ki-67 on a low significance level (bivariate analysis: r = -0.160, p = 0.040). There was only a weak correlation between the ADC-values measured in the breast target lesions and HER2-expression (bivariate ansalysis: r = 0.191, p = 0.030)., Conclusions: Our preliminary results indicate that evaluation of perfusion based DLCT-data and MRI-biomarkers show correlations with the immunhistochemical subtyping of invasive ductal breast carcinomas. Further clinical research is warranted in order to validate the value of the results and define clinical situations in which the use of the described DLCT-biomaker and MRI biomarkers may be helpful in clinical patient care., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: In the management of cancer patients, determination of TNM status is essential for treatment decision-making and therefore closely linked to clinical outcome and survival. Here, we developed a tool for automatic three-dimensional (3D) localization and segmentation of cervical lymph nodes (LNs) on contrast-enhanced computed tomography (CECT) examinations., Methods: In this IRB-approved retrospective single-center study, 187 CECT examinations of the head and neck region from patients with various primary diseases were collected from our local database, and 3656 LNs (19.5 ± 14.9 LNs/CECT, mean ± standard deviation) with a short-axis diameter (SAD) ≥ 5 mm were segmented manually by expert physicians. With these data, we trained an independent fully convolutional neural network based on 3D foveal patches. Testing was performed on 30 independent CECTs with 925 segmented LNs with an SAD ≥ 5 mm., Results: In total, 4,581 LNs were segmented in 217 CECTs. The model achieved an average localization rate (LR), i.e., percentage of localized LNs/CECT, of 78.0% in the validation dataset. In the test dataset, average LR was 81.1% with a mean Dice coefficient of 0.71. For enlarged LNs with a SAD ≥ 10 mm, LR was 96.2%. In the test dataset, the false-positive rate was 2.4 LNs/CECT., Conclusions: Our trained AI model demonstrated a good overall performance in the consistent automatic localization and 3D segmentation of physiological and metastatic cervical LNs with a SAD ≥ 5 mm on CECTs. This could aid clinical localization and automatic 3D segmentation, which can benefit clinical care and radiomics research., Relevance Statement: Our AI model is a time-saving tool for 3D segmentation of cervical lymph nodes on contrast-enhanced CT scans and serves as a solid base for N staging in clinical practice and further radiomics research., Key Points: • Determination of N status in TNM staging is essential for therapy planning in oncology. • Segmenting cervical lymph nodes manually is highly time-consuming in clinical practice. • Our model provides a robust, automated 3D segmentation of cervical lymph nodes. • It achieves a high accuracy for localization especially of enlarged lymph nodes. • These segmentations should assist clinical care and radiomics research., (© 2023. The Author(s).)

Background: Osteosarcoma and Ewing's sarcoma in children and adolescents require age-specific interdisciplinary diagnosis and treatment to achieve optimal therapeutic outcomes., Methods: The diagnosis and treatment of malignant bone tumors in childhood and adolescence are presented in the light of publications retrieved by a selective search, pertinent guidelines, and the authors' extensive experience in an interdisciplinary cancer center., Results: Bone sarcomas make up approximately 5% of all malignancies in children and adolescents; the most common types are Ewing's sarcoma and osteosarcoma. Patients are often not referred to a specialized center until long after the onset of symptoms, as they and their physicians rarely consider the possibility of a bone tumor, and the symptoms are often trivialized. Bone pain of unknown origin, swelling, and functional limitations should be investigated with conventional x-rays. Lesions of unclear origin should be biopsied after a meticulous clinical and radiologic evaluation. Multimodal treatment consists of neo - adjuvant chemotherapy, limb-preserving resection if possible, and radiotherapy where indicated. In multicenter studies, patients with osteosarcoma achieve event-free survival in 64% of cases if their disease is localized, and 28% if it is metastatic; the corresponding figures for patients with Ewing's sarcoma are 80% and 27%, respectively., Conclusion: With implementation of the current treatment recommendations, most children and adolescents with malignant bone tumors can be treated successfully with curative intent. These patients should be referred to a sarcoma center for diagnosis and treatment.

Desmoid tumors are a rare form of cancer, which show locally aggressive invasion of surrounding tissues and may occur anywhere in the body. Treatment options comprise conservative watch and wait strategies as tumors may show spontaneous regression as well as surgical resection, radiation therapy, nonsteroidal anti-inflammatory drugs (NSAID), chemotherapy, or local thermoablative approaches for progressive disease. The latter comprises cryotherapy, radiofrequency, microwave ablation, or thermal ablation with high intensity focused ultrasound (HIFU) as the only entirely non-invasive option. This report presents a case where a desmoid tumor at the left dorsal humerus was 2 times surgically resected and, after recurrence, thermally ablated with HIFU under magnetic resonance image-guidance (MR-HIFU). In our report, we analyze tumor volume and/or pain score during standard of care (2 years) and after HIFU treatment over a 4-year follow-up period. Results showed MR-HIFU treatment led to complete tumor remission and pain response., Competing Interests: Author SY is partly employed by Profound Medical. The content of this work is outside the scope of her company work. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Yeo, Bratke, Knöll, Walter, Maintz and Grüll.)

Published under a CC BY 4.0 license.

Objectives: Differentiation between COVID-19 and community-acquired pneumonia (CAP) in computed tomography (CT) is a task that can be performed by human radiologists and artificial intelligence (AI). The present study aims to (1) develop an AI algorithm for differentiating COVID-19 from CAP and (2) evaluate its performance. (3) Evaluate the benefit of using the AI result as assistance for radiological diagnosis and the impact on relevant parameters such as accuracy of the diagnosis, diagnostic time, and confidence., Methods: We included n = 1591 multicenter, multivendor chest CT scans and divided them into AI training and validation datasets to develop an AI algorithm (n = 991 CT scans; n = 462 COVID-19, and n = 529 CAP) from three centers in China. An independent Chinese and German test dataset of n = 600 CT scans from six centers (COVID-19 / CAP; n = 300 each) was used to test the performance of eight blinded radiologists and the AI algorithm. A subtest dataset (180 CT scans; n = 90 each) was used to evaluate the radiologists' performance without and with AI assistance to quantify changes in diagnostic accuracy, reporting time, and diagnostic confidence., Results: The diagnostic accuracy of the AI algorithm in the Chinese-German test dataset was 76.5%. Without AI assistance, the eight radiologists' diagnostic accuracy was 79.1% and increased with AI assistance to 81.5%, going along with significantly shorter decision times and higher confidence scores., Conclusion: This large multicenter study demonstrates that AI assistance in CT-based differentiation of COVID-19 and CAP increases radiological performance with higher accuracy and specificity, faster diagnostic time, and improved diagnostic confidence., Key Points: • AI can help radiologists to get higher diagnostic accuracy, make faster decisions, and improve diagnostic confidence. • The China-German multicenter study demonstrates the advantages of a human-machine interaction using AI in clinical radiology for diagnostic differentiation between COVID-19 and CAP in CT scans., (© 2022. The Author(s), under exclusive licence to European Society of Radiology.)

Objectives: To evaluate the feasibility of combining compressed sense (CS) with a newly developed deep learning-based algorithm (CS-AI) using convolutional neural networks to accelerate 2D MRI of the knee., Methods: In this prospective study, 20 healthy volunteers were scanned with a 3T MRI scanner. All subjects received a fat-saturated sagittal 2D proton density reference sequence without acceleration and four additional acquisitions with different acceleration levels: 2, 3, 4 and 6. All sequences were reconstructed with the conventional CS and a new CS-AI algorithm. Two independent, blinded readers rated all images by seven criteria (overall image impression, visible artifacts, delineation of anterior ligament, posterior ligament, menisci, cartilage, and bone) using a 5-point Likert scale. Signal- and contrast-to-noise ratios were calculated. Subjective ratings and quantitative metrics were compared between CS and CS-AI with similar acceleration levels and between all CS/CS-AI images and the non-accelerated reference sequence. Friedman and Dunn´s multiple comparison tests were used for subjective, ANOVA and the Tukey Kramer test for quantitative metrics., Results: Conventional CS images at the lowest acceleration level (CS2) were already rated significantly lower than reference for 6/7 criteria. CS-AI images maintained similar image quality to the reference up to CS-AI three for all criteria, which would allow for a reduction in scan time of 64% with unchanged image quality compared to the unaccelerated sequence. SNR and CNR were significantly higher for all CS-AI reconstructions compared to CS (all p < 0.05)., Conclusions: AI-based image reconstruction showed higher image quality than CS for 2D knee imaging. Its implementation in the clinical routine yields the potential for faster MRI acquisition but needs further validation in non-healthy study subjects., Advances in Knowledge: Combining compressed SENSE with a newly developed deep learning-based algorithm using convolutional neural networks allows a 64% reduction in scan time for 2D imaging of the knee. Implementation of the new deep learning-based algorithm in clinical routine in near future should enable better image quality/resolution with constant scan time, or reduced acquisition times while maintaining diagnostic quality., Competing Interests: Conflict of interestThe author Kristina Sonnabend currently works for Philips GmbH Market DACH, Hamburg, Germany. David Maintz and Nils Große Hokamp are on the speaker’s bureau of Philips Healthcare. Nils Große Hokamp and Simon Lennartz receive research support from Philips Healthcare. The remaining authors have no potential conflict of interest to declare.

Purpose: The bone marrow's iodine uptake in dual-energy CT (DECT) is elevated in malignant disease. We aimed to investigate the physiological range of bone marrow iodine uptake after intravenous contrast application, and examine its dependence on vBMD, iodine blood pool, patient age, and sex., Method: Retrospective analysis of oncological patients without evidence of metastatic disease. DECT examinations were performed on a spectral detector CT scanner in portal venous contrast phase. The thoracic and lumbar spine were segmented by a pre-trained neural network, obtaining volumetric iodine concentration data [mg/ml]. vBMD was assessed using a phantomless, CE-certified software [mg/cm3]. The iodine blood pool was estimated by ROI-based measurements in the great abdominal vessels. A multivariate regression model was fit with the dependent variable "median bone marrow iodine uptake". Standardized regression coefficients (β) were calculated to assess the impact of each covariate., Results: 678 consecutive DECT exams of 189 individuals (93 female, age 61.4 ± 16.0 years) were evaluated. AI-based segmentation provided volumetric data of 97.9% of the included vertebrae (n=11,286). The 95 th percentile of bone marrow iodine uptake, as a surrogate for the upper margin of the physiological distribution, ranged between 4.7-6.4 mg/ml. vBMD (p <0.001, mean β=0.50) and portal vein iodine blood pool (p <0.001, mean β=0.43) mediated the strongest impact. Based thereon, adjusted reference values were calculated., Conclusion: The bone marrow iodine uptake demonstrates a distinct profile depending on vBMD, iodine blood pool, patient age, and sex. This study is the first to provide the adjusted reference values., Competing Interests: DZ and NG-H received research support from Philips Healthcare unrelated to this project. DM and NG-H are on the speakers bureau of Philips Healthcare. NH-H is a consultant for Bristol Myers Squibb. The other authors have no conflict of interest to declare. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Fervers, Fervers, Rinneburger, Weisthoff, Kottlors, Reimer, Zopfs, Celik, Maintz, Große-Hokamp and Persigehl.)

The radiologic evaluation of the sagittal angulation of the distal humerus is commonly based on standard lateral radiographs. However, lateral radiographs do not allow to examine the lateral angulation of the capitulum and the trochlea, separately. Although this problem could be approached via computed tomography, there are no data available describing the difference between the angulation of the capitulum and trochlea. Therefore, we aimed to assess sagittal angles of the capitulum and trochlea in relation to the humeral shaft based on 400 CT-scans of the elbow in healthy adults. Angles were measured in sagittal planes at the capitulum center and three anatomically defined trochlea locations and were spanned between the axis of the joint component and the humerus shaft. Angles were tested for differences between measurement locations and correlation with patient characteristics (age, sex, trans-epicondylar distance). Angles increased from lateral to medial measurement locations (107.4 ± 9.6°, 167.4 ± 8.2°, 171.8 ± 7.3°, 179.1 ± 7.0°; p < 0.05). Largest angle differences were detected between the capitulum and trochlea with smallest angles measured at the capitulum. Patient characteristics did not correlate with angles (p > 0.05). Intra-rater-reliability was r = 0.79-0.86. As CT-imaging allows to distinguish between sagittal capitulum and trochlea locations, it might benefit the radiologic diagnostic of sagittal malalignments of the distal humerus at the capitulum and trochlea, separately., (© 2023. The Author(s).)

Background Automation bias (the propensity for humans to favor suggestions from automated decision-making systems) is a known source of error in human-machine interactions, but its implications regarding artificial intelligence (AI)-aided mammography reading are unknown. Purpose To determine how automation bias can affect inexperienced, moderately experienced, and very experienced radiologists when reading mammograms with the aid of an artificial intelligence (AI) system. Materials and Methods In this prospective experiment, 27 radiologists read 50 mammograms and provided their Breast Imaging Reporting and Data System (BI-RADS) assessment assisted by a purported AI system. Mammograms were obtained between January 2017 and December 2019 and were presented in two randomized sets. The first was a training set of 10 mammograms, with the correct BI-RADS category suggested by the AI system. The second was a set of 40 mammograms in which an incorrect BI-RADS category was suggested for 12 mammograms. Reader performance, degree of bias in BI-RADS scoring, perceived accuracy of the AI system, and reader confidence in their own BI-RADS ratings were assessed using analysis of variance (ANOVA) and repeated-measures ANOVA followed by post hoc tests and Kruskal-Wallis tests followed by the Dunn post hoc test. Results The percentage of correctly rated mammograms by inexperienced (mean, 79.7% ± 11.7 [SD] vs 19.8% ± 14.0; P < .001; r = 0.93), moderately experienced (mean, 81.3% ± 10.1 vs 24.8% ± 11.6; P < .001; r = 0.96), and very experienced (mean, 82.3% ± 4.2 vs 45.5% ± 9.1; P = .003; r = 0.97) radiologists was significantly impacted by the correctness of the AI prediction of BI-RADS category. Inexperienced radiologists were significantly more likely to follow the suggestions of the purported AI when it incorrectly suggested a higher BI-RADS category than the actual ground truth compared with both moderately (mean degree of bias, 4.0 ± 1.8 vs 2.4 ± 1.5; P = .044; r = 0.46) and very (mean degree of bias, 4.0 ± 1.8 vs 1.2 ± 0.8; P = .009; r = 0.65) experienced readers. Conclusion The results show that inexperienced, moderately experienced, and very experienced radiologists reading mammograms are prone to automation bias when being supported by an AI-based system. This and other effects of human and machine interaction must be considered to ensure safe deployment and accurate diagnostic performance when combining human readers and AI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Baltzer in this issue.

Background: Structured reporting allows a high grade of standardization and thus a safe and unequivocal report communication. In the past years, the radiological societies have started several initiatives to base radiological reports on structured reporting rather than free text reporting., Methods: Upon invitation of the working group for Cardiovascular Imaging of the German Society of Radiology, in 2018 an interdisciplinary group of Radiologists, Cardiologists, Pediatric Cardiologists and Cardiothoracic surgeons -all experts on the field of cardiovascular MR and CT imaging- met for interdisciplinary consensus meetings at the University Hospital Cologne. The aim of these meetings was to develop and consent templates for structured reporting in cardiac MR and CT of various cardiovascular diseases., Results: Two templates for structured reporting of CMR in ischemia imaging and vitality imaging and two templates for structured reporting of CT imaging for planning Transcatheter Aortic Valve Implantation (TAVI; pre-TAVI-CT) and coronary CT were discussed, consented and transferred to a HTML 5/IHR MRRT compatible format. The templates were made available for free use on the website www.befundung.drg.de., Conclusion: This paper suggests consented templates in German language for the structured reporting of cross-sectional CMR imaging of ischemia and vitality as well as reporting of CT imaging pre-TAVI and coronary CT. The implementation of these templates is aimed at providing a constant level of high reporting quality and increasing the efficiency of report generation as well as a clinically based communication of imaging results., Key Points: · Structured reporting offers a constant level of high reporting quality and increases the efficiency of report generation as well as a clinically based communication of imaging results.. · For the first time templates in German language for the structured reporting of CMR imaging of ischemia and vitality and CT imaging pre-TAVI and coronary CT are reported.. · These templates will be made available on the website www.befundung.drg.de and can be commented via strukturierte-befundung@drg.de.., Zitierweise: · Soschynski M, Bunck AC, Beer M et al. Structured Reporting in Cross-Sectional Imaging of the Heart: Reporting Templates for CMR Imaging of Ischemia and Myocardial Viability and for Cardiac CT Imaging of Coronary Heart Disease and TAVI Planning. Fortschr Röntgenstr 2023; 195: 293 - 296., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Objectives: To systematically investigate the usability of virtual non-contrast reconstructions (VNC) derived from dual-layer CT (DLCT) for detection and size measurements of kidney stones with regards to different degrees of surrounding iodine-induced attenuation and radiation dose., Methods: Ninety-two kidney stones of varying size (3-14 mm) and composition were placed in a phantom filled with different contrast media/water mixtures exhibiting specific iodine-induced attenuation (0-1500 HU). DLCT-scans were acquired using CTDI vol of 2 mGy and 10 mGy. Conventional images (CI) and VNC 0H-1500HU were reconstructed. Reference stone size was determined using a digital caliper (Man-M). Visibility and stone size were assessed. Statistical analysis was performed using the McNemar test, Wilcoxon test, and the coefficient of determination., Results: All stones were visible on CI 0HU and VNC 200HU . Starting at VNC 400 HU , the detection rate decreased with increasing HU and was significantly lower as compared to CI 0HU on VNC ≥ 600HU (100.0 vs. 94.0%, p < 0.05). The overall detection rate was higher using 10 mGy as compared to 2 mGy protocol (87.9 vs. 81.8%; p < 0.001). Stone size was significantly overestimated on all VNC compared to Man-M (7.0 ± 3.5 vs. 6.6 ± 2.8 mm, p < 0.001). Again, the 10 mGy protocol tended to show a better correlation with Man-M as compared to 2 mGy protocol (R 2 = 0.39-0.68 vs. R 2 = 0.31-0.57)., Conclusions: Detection and size measurements of kidney stones surrounded by contrast media on VNC are feasible. The detection rate of kidney stones decreases with increasing iodine-induced attenuation and with decreasing radiation dose as well as stone size, while remaining comparable to CI 0HU on VNC ≤ 400 HU ., Key Points: • The detection rate of kidney stones on VNC depends on the surrounding iodine-induced attenuation, the used radiation dose, and the stone size. • The detection rate of kidney stones on VNC decreases with greater iodine-induced attenuation and with lower radiation dose, particularly in small stones. • The visibility of kidney stones on VNC ≤ 400 HU remains comparable to true-non-contrast scans even when using a low-dose technique., (© 2022. The Author(s).)

Background: Diagnosing a coronavirus disease 2019 (COVID-19) infection with high specificity in chest computed tomography (CT) imaging is considered possible due to distinctive imaging features of COVID-19 pneumonia. Since other viral non-COVID pneumonia show mostly a different distribution pattern, it is reasonable to assume that the patterns observed caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are a consequence of its genetically encoded molecular properties when interacting with the respiratory tissue. As more mutations of the initial SARS-CoV-2 wild-type with varying aggressiveness have been detected in the course of 2021, it became obvious that its genome is in a state of transformation and therefore a potential modification of the specific morphological appearance in CT may occur. The aim of this study was to quantitatively analyze the morphological differences of the SARS-CoV-2-B.1.1.7 mutation and wildtype variant in CT scans of the thorax., Methods: We analyzed a dataset of 140 patients, which was divided into pneumonias caused by n=40 wildtype variants, n=40 B.1.1.7 variants, n=20 bacterial pneumonias, n=20 viral (non-COVID) pneumonias, and a test group of n=20 unremarkable CT examinations of the thorax. Semiautomated 3D segmentation of the lung tissue was performed for quantification of lung pathologies. The extent, ratio, and specific distribution of inflammatory affected lung tissue in each group were compared in a multivariate group analysis., Results: Lung segmentation revealed significant difference between the extent of ground glass opacities (GGO) or consolidation comparing SARS-CoV-2 wild-type and B.1.1.7 variant. Wildtype and B.1.1.7 variant showed both a symmetric distribution pattern of stage-dependent GGO and consolidation within matched COVID-19 stages. Viral non-COVID pneumonias had significantly fewer consolidations than the bacterial, but also than the COVID-19 B.1.1.7 variant groups., Conclusions: CT based segmentation showed no significant difference between the morphological appearance of the COVID-19 wild-type variant and the SARS-CoV-2 B.1.1.7 mutation. However, our approach allowed a semiautomatic quantification of bacterial and viral lung pathologies. Quantitative CT image analyses, such as the one presented, appear to be an important component of pandemic preparedness considering an organism with ongoing genetic change, to describe a potential arising change in CT morphological appearance of possible new upcoming COVID-19 variants of concern., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-22-718/coif). DM received speaker’s honoria from Philips Healthcare, unrelated to the presented work. RS is an employee of Philips Healthcare unrelated to the presented work, there is no direct or indirect influence on the result of the present work. The other authors have no conflicts of interest to declare., (2023 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

This position paper is a joint statement of the German Radiological Society (DRG) and the Professional Association of German Radiologists (BDR), which reflects the current state of knowledge about coronary computed tomography (CT). It is based on preclinical and clinical studies that have investigated the clinical relevance as well as the technical requirements and fundamentals of cardiac computed tomography., (© 2022. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

This position paper is a joint statement of the German Radiological Society (DRG) and the Professional Association of German Radiologists (BDR), which reflects the current state of knowledge about coronary computed tomography. It is based on preclinical and clinical studies that have investigated the clinical relevance as well as the technical requirements and fundamentals of cardiac computed tomography. CITATION FORMAT: · Langenbach MC, Sandstede J, Sieren M et al. DRG and BDR Position Paper on Coronary CT: Clinical Evidence and Quality of Patient Care in Chronic Coronary Syndrome. Fortschr Röntgenstr 2023; 195: 115 - 133., Competing Interests: Fabian Bamberg: Bayer Healthcare (Unrestricted Research Grant, Speakers Bureau, Consulting), Siemens Healthineers (Unrestricted Research Grant, Speakers Bureau)., (Thieme. All rights reserved.)

Purpose: To evaluate the clinical applicability of a prototype virtual non-contrast (VNC) reconstruction algorithm based on coronary CT angiography (cCTA) to assess calcified coronary plaques by calcium scoring (CACS)., Methods: Eighty consecutive patients suspected of coronary artery disease were retrospectively included. All patients underwent a cardiac CT using a dual-layer spectral-detector CT system. The standardized acquisition protocol included unenhanced CACS and cCTA. Datasets were acquired using 120 keV. VNC-reconstructions were calculated from the cCTA images at 2.5 mm (VNC group 1), 2.5 of 0.9 mm (group 2), and 0.9 mm (group 3) slice thickness. We compared the Agatston score and Coronary Artery Calcium Data and Reporting System (CAC-DRS) of all VNC reconstructions with the true non-contrast (TNC)-dataset as the gold standard., Results: In total, 73 patients were evaluated. Fifty patients (68.5 %) had a CACS > 0 based on TNC. We found a significant difference in the Agatston score comparing all VNC-reconstructions (1: 1.35, 2: 3.7, 3: 10.4) with the TNC dataset (3.8) (p < 0.001). Correlation analysis of the datasets showed an excellent correlation of the TNC results with the different VNC-reconstructions (r = 0.904-0.974, p < 0.001) with a slope of 1.89-2.53. Mean differences and limits of agreement by Bland-Altman analysis between TNC and group 1 were 83 and -196 to 362, respectively. By using the VNC-reconstructions, in group 1 23 patients (31.5 %), in group 2 10 (13.7 %), and in group 3 23 (31.5 %) were reclassified according to CAC-DRS compared to TNC. Classification according to CAC-DRS revealed a significant difference between TNC and group 1 (p = 0.024) and no significance compared to groups 2 and 3 (p = 0.670 and 0.273)., Conclusion: The investigated VNC reconstruction algorithm of routine cCTA allows the detection and evaluation of coronary calcium burden without the requirement for an additional acquisition of an unenhanced CT scan for CACS and, therefore, a reduction of radiation exposure., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [EL and GP are employees of Philips Healthcare. The other authors have no conflict of interest to disclose.], (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Magnetic resonance imaging (MRI) is currently explored as supplemental tool to monitor disease progression and treatment response in various neuromuscular disorders. We here assessed the utility of a multi-parametric magnetic resonance imaging (MRI) protocol including quantitative water T 2 mapping, Dixon-based proton density fat fraction (PDFF) estimation and diffusion tensor imaging (DTI) to detect loss of spinal motor neurons and subsequent muscle damage in adult SMA patients., Methods: Sixteen SMA patients and 13 age-matched controls were enrolled in this prospective, longitudinal study. All participants underwent MRI imaging including measurements of Dixon-based PDFF and DTI of the sciatic nerve. SMA patients furthermore underwent measurements of muscle water T 2 (T 2w ) of the biceps femoris muscle (BFM) and quadriceps femoris muscle (QFM). Ten participants returned for a second scan six months later. MRI parameter were correlated with clinical data. All patients were on nusinersen treatment., Results: There were significantly higher intramuscular fat fractions in the BFM and QFM of SMA patients compared to healthy controls at baseline and after 6 months. Furthermore, T2 values significantly correlated positively with intramuscular fat fractions. The Hammersmith functional motor scale significantly correlated with the QFM's intramuscular fat fractions. DTI scans of the sciatic nerve were not significantly different between the two groups., Conclusion: This study demonstrates that, water T 2 mapping and Dixon-based PDFF estimation may distinguish between adult SMA patients and controls, due to massive intramuscular fat accumulation in SMA. More extensive long-term studies are warranted to further evaluate these two modalities as surrogate markers in SMA patients during treatment., (© 2022. The Author(s).)

Autosomal dominant polycystic kidney disease (ADPKD) is the most common monogenic kidney disease. Patients at high risk of severe disease progression should be identified early in order to intervene with supportive and therapeutic measures. However, the glomerular filtration rate (GFR) may remain within normal limits for decades until decline begins, making it a late indicator of rapid progression. Kidney volumetry is frequently used in clinical practice to allow for an assessment of disease severity. Due to limited prognostic accuracy, additional imaging markers are of high interest to improve outcome prediction in ADPKD, but data from clinical cohorts are still limited. In this study, we examined cyst fraction as one of these parameters in a cohort of 142 ADPKD patients. A subset of 61 patients received MRIs in two consecutive years to assess longitudinal changes. All MRIs were analyzed by segmentation and volumetry of the kidneys followed by determination of cyst fraction. As expected, both total kidney volume (TKV) and cyst fraction correlated with estimated GFR (eGFR), but cyst fraction showed a higher R 2 in a univariate linear regression. Besides, only cyst fraction remained statistically significant in a multiple linear regression including both htTKV and cyst fraction to predict eGFR. Consequently, this study underlines the potential of cyst fraction in ADPKD and encourages prospective clinical trials examining its predictive value in combination with other biomarkers to predict future eGFR decline.

Deep inferior epigastric artery flaps (DIEP) represent the gold standard of autologous breast reconstruction. Due to significant variations in vascular anatomy, preoperative perforator mapping (PM) is mandatory in order to ensure the presence of a sufficient perforator within the flap. In this regard, CT angiography (CTA) is currently the method of choice. Therefore, we investigated the value of contrast-enhanced ultrasound (CEUS) techniques for preoperative PM in comparison to CTA. Patients underwent PM, utilizing both CTA and CEUS techniques. Documentation included the course of the vascular pedicle through the rectus muscle (M), fascial penetration (F), the subcutaneous plexus (P) and the skin point (SP) on either side of the abdomen. Thus, contrast-enhanced B-Flow (BCEUS), B-Flow ultrasound (BUS), CEUS, color Doppler ultrasound (CDUS) and CTA were evaluated in terms of the diagnostic consistency and effectiveness of PM. Precision (∆L) was then calculated in relation to the actual intraoperative location. Statistical analysis included Kruskall-Wallis, Levene and Bonferroni tests, as well as Spearman correlations. A total of 39 DIEP flaps were analyzed. Only CTA (∆L = 2.85 mm) and BCEUS (∆L = 4.57 mm) enabled complete PM, also including P and SP, whereas CDUS, CEUS and BUS enabled clear PM throughout M and F only. Regarding the number of detected perforators, PM techniques are ranked from high to low as follows: CTA, BCEUS, BUS, CEUS and CDUS. CTA and BCEUS showed sufficient diagnostic consistency for SP, P and F, while CDUS and CTA had a superior performance for M. BCEUS offers precise image-controlled surface tags and dynamic information for PM without imposing radiation and may, therefore, be considered a feasible add-on or alternative to CTA. However, BCEUS requires an experienced examiner and is more time-consuming.

Background: The extent of lung involvement in coronavirus disease 2019 (COVID-19) pneumonia, quantified on computed tomography (CT), is an established biomarker for prognosis and guides clinical decision-making. The clinical standard is semi-quantitative scoring of lung involvement by an experienced reader. We aim to compare the performance of automated deep-learning- and threshold-based methods to the manual semi-quantitative lung scoring. Further, we aim to investigate an optimal threshold for quantification of involved lung in COVID pneumonia chest CT, using a multi-center dataset., Methods: In total 250 patients were included, 50 consecutive patients with RT-PCR confirmed COVID-19 from our local institutional database, and another 200 patients from four international datasets (n=50 each). Lung involvement was scored semi-quantitatively by three experienced radiologists according to the established chest CT score (CCS) ranging from 0-25. Inter-rater reliability was reported by the intraclass correlation coefficient (ICC). Deep-learning-based segmentation of ground-glass and consolidation was obtained by CT Pulmo Auto Results prototype plugin on IntelliSpace Discovery (Philips Healthcare, The Netherlands). Threshold-based segmentation of involved lung was implemented using an open-source tool for whole-lung segmentation under the presence of severe pathologies (R231CovidWeb, Hofmanninger et al. , 2020) and consecutive quantitative assessment of lung attenuation. The best threshold was investigated by training and testing a linear regression of deep-learning and threshold-based results in a five-fold cross validation strategy., Results: Median CCS among 250 evaluated patients was 10 [6-15]. Inter-rater reliability of the CCS was excellent [ICC 0.97 (0.97-0.98)]. Best attenuation threshold for identification of involved lung was -522 HU. While the relationship of deep-learning- and threshold-based quantification was linear and strong (r 2 deep-learning vs. threshold =0.84), both automated quantification methods translated to the semi-quantitative CCS in a non-linear fashion, with an increasing slope towards higher CCS (r 2 deep-learning vs. CCS = 0.80, r 2 threshold vs. CCS =0.63)., Conclusions: The manual semi-quantitative CCS underestimates the extent of COVID pneumonia in higher score ranges, which limits its clinical usefulness in cases of severe disease. Clinical implementation of fully automated methods, such as deep-learning or threshold-based approaches (best threshold in our multi-center dataset: -522 HU), might save time of trained personnel, abolish inter-reader variability, and allow for truly quantitative, linear assessment of COVID lung involvement., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-22-175/coif). DM is on the speaker’s bureau of Philips Healthcare. HC and RS are employees of Philips Healthcare. The other authors have no conflicts of interest to declare., (2022 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Objective: To examine the correlation of quantitative measurements from material decomposition maps calculated from dual-layer CT (DLCT)-image datasets with immunohistochemical biomarkers of invasive breast carcinomas., Material and Methods: All patients at the University Breast Cancer Center who underwent a clinically indicated dual-layer CT-scan for staging of invasive ductal breast carcinoma from 01/2016 to 07/2020 were prospectively included. Iodine concentration maps and maps of the effective atomic numbers (Zeffective) were reconstructed from the image datasets. ROI-based evaluations of the index tumors and predefined references tissues for normalization were performed semi-automatically in identical anatomical positions using dedicated evaluation software. Statistical analysis was essentially descriptive using Spearmańs rank correlation and (multivariable) partial correlation., Results: Bivariate showed statistically significant correlations of iodine contents (r = -0.154/-0.202/0.180, p = 0.039/0.006/0.015), and Zeffective-values (r = -0.158/-0.199/0.179, p = 0.034/0.007/0.016) for all 184 carcinomas and the subgroup of 168 invasive ductal carcinomas. The results were confirmed by multivariate analyses with "age", "diameter" and "ACR-grade" as possible confounders. Normalization of the measured target values with those in the aorta confirmed significant correlations of iodine content and Zeffective compared to Estrogen (r = 0.174, p = 0.019), Progesteron (r = 0.168/0.177, p = 0.024/0.017), and HER2 receptor expression (r = -0.222/-0.184, p = 0.003/0.013). All CT-parameters showed significant correlations with immunohistochemical subtyping (r = 0.191/0.192, p = 0.010)., Conclusions: Our preliminary results indicate that iodine content and Zeffective-values derived from DLCT-examinations correlate with hormone receptor expression in invasive breast carcinomas. Assignments to benign entities already seam feasible in clinical routine CT-diagnostics. After further investigations iodine content and Zeffective may be translated as diagnostical and prognostical biomarkers into clinical routine in the long term., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Objective: The aim of this study was to investigate the impact of left atrial diverticula (LADs), left sided septal pouches (LSSPs) and middle right pulmonary veins (MRPVs) on recurrent atrial fibrillation (rAF) in patients undergoing laser pulmonary vein isolation procedure (PVI)., Material and Methods: This retrospective study enrolled 139 patients with pre-procedural multiple detector computed tomography (MDCT) imaging and 12 months follow-up examination. LADs, LSSPs and MRPV were identified by two radiologists on a dedicated workstation using multiplanar reconstructions and volume rendering technique. Univariate and bivariate regression analyses with patient demographics and cardiovascular risk factors as covariates were performed to reveal independent factors associated with rAF., Results: LADs were recorded in 41 patients (29%), LSSPs in 20 (14%) and MRPVs in 15 (11%). The right anterosuperior wall of the left atrium was the most prevalent location of LADs (68%). rAF occured in 20 patients, thereof, 15 exhibited an outpouching structure of the left atrium (LAD: 9, LSSP: 2 and MRPV: 3). Presence of an LAD (HR: 2.7, 95%CI: 1.0-8.4, p = 0.04) and permanent AF (HR: 4.8, 95%CI: 1.5-16.3, p = 0.01) were independently associated with rAF., Conclusions: LAD, LSSP and MRPV were common findings on pre-procedural cardiac computed tomography. LADs were revealed as potential independent risk factor of rAF, which might be considered for treatment planning and post-treatment observation., Competing Interests: The authors have declared that no competing interests exist.